Lipid peroxidation yields a variety of electrophiles, which are thought to contribute to the molecular pathogenesis of diseases involving oxidative stress, yet little is known of the scope of protein damage caused by lipid electrophiles. We identified protein targets of the prototypical lipid electrophile 4-hydroxy-2-nonenal (HNE) in RKO cells treated with 50 or 100 mum HNE. HNE Michael adducts were biotinylated by reaction with biotinamidohexanoic acid hydrazide, captured with streptavidin, and the captured proteins were resolved by one dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis, digested with trypsin, and identified by liquid chromatography-tandem mass spectrometry. Of the 1500+ proteins identified, 417 displayed a statistically significant increase in adduction with increasing HNE exposure concentration. We further identified 18 biotin hydrazide-modified, HNE-adducted peptides by specific capture using anti-biotin antibody and analysis by high resolution liquid chromatography-tandem mass spectrometry. A subset of the identified HNE targets were validated with a streptavidin capture and immunoblotting approach, which enabled detection of adducts at HNE exposures as low as 1 mum. Protein interaction network analysis indicated several subsystems impacted by endogenous electrophiles in oxidative stress, including the 26 S proteasomal and chaperonin containing TCP-1 (CCT) systems involved in protein-folding and degradation, as well as the COP9 signalosome, translation initiation complex, and a large network of ribonucleoproteins. Global analyses of protein lipid electrophile adducts provide a systems-level perspective on the mechanisms of diseases involving oxidative stress.

Understanding proteomic differences underlying the different phenotypic classes of colon and rectal carcinoma is important and may eventually lead to a better assessment of clinical behavior of these cancers. We here present a comprehensive description of the proteomic data obtained from 90 colon and rectal carcinomas previously subjected to genomic analysis by The Cancer Genome Atlas (TCGA). Here, the primary instrument files and derived secondary data files are compiled and presented in forms that will allow further analyses of the biology of colon and rectal carcinoma. We also discuss new challenges in processing these large proteomic datasets for relevant proteins and protein variants.

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens to hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility, and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here, we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and seven control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data, we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to subnanogram/ml sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and interlaboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy-isotope-labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an interlaboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality control measures, enables sensitive, specific, reproducible, and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation (source code is available from http://homepages.uc.edu/~wang2x7/Research.htm ). From these assessments, we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61 to 93% of the time. When comparing across different instruments and quantitative technologies, using multiple replicates, differential genes were reproduced by other data sets from 67 to 99% of the time. Projecting gene differences to biological pathways and networks increased the degree of similarity. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.

Liquid chromatography tandem mass spectrometry (LC-MS/MS) based methods provide powerful tools for the quantitative analysis of modified proteins. We have developed a label-free approach using internal reference peptides (IRP) from the target protein for signal normalization without the need for isotope labeling. Ion-trap mass spectrometry and pseudo-selected reaction monitoring (pSRM) were used to acquire full MS/MS and MS(3) spectra from target peptides. Skyline, a widely used software for SRM experiments, was used for chromatographic ion extraction. Phosphopeptides spiked into a BSA background yielded concentration response curves with high correlation coefficients (typically >0.9) and low coefficients of variation (≤15%) over a 200-fold concentration range. Stable isotope dilution (SID) and IRP methods were compared for quantitation of six site-specific phosphorylations in the epidermal growth factor receptor (EGFR) in epidermal growth factor-stimulated A431 cells with or without the addition of EGFR inhibitors cetuximab and gefitinib. Equivalent responses were observed with both IRP and SID methods, although analyses using the IRP method typically had higher median CVs (22-31%) than SID (10-20%). Analyses using both methods were consistent with immunoblot using site-selective antibodies. The ease of implementation and the suitability for targeted quantitative comparisons make this method suitable for broad application in protein biochemistry.

Analysis of cellular signaling networks typically involves targeted measurements of phosphorylated protein intermediates. However, phosphoproteomic analyses usually require affinity enrichment of phosphopeptides and can be complicated by artifactual changes in phosphorylation caused by uncontrolled preanalytical variables, particularly in the analysis of tissue specimens. We asked whether changes in protein expression, which are more stable and easily analyzed, could reflect network stimulation and inhibition. We employed this approach to analyze stimulation and inhibition of the epidermal growth factor receptor (EGFR) by EGF and selective EGFR inhibitors. Shotgun analysis of proteomes from proliferating A431 cells, EGF-stimulated cells, and cells co-treated with the EGFR inhibitors cetuximab or gefitinib identified groups of differentially expressed proteins. Comparisons of these protein groups identified 13 proteins whose EGF-induced expression changes were reversed by both EGFR inhibitors. Targeted multiple reaction monitoring analysis verified differential expression of 12 of these proteins, which comprise a candidate EGFR inhibition signature. We then tested these 12 proteins by multiple reaction monitoring analysis in three other models: 1) a comparison of DiFi (EGFR inhibitor-sensitive) and HCT116 (EGFR-insensitive) cell lines, 2) in formalin-fixed, paraffin-embedded mouse xenograft DiFi and HCT116 tumors, and 3) in tissue biopsies from a patient with the gastric hyperproliferative disorder Ménétrier's disease who was treated with cetuximab. Of the proteins in the candidate signature, a core group, including c-Jun, Jagged-1, and Claudin 4, were decreased by EGFR inhibitors in all three models. Although the goal of these studies was not to validate a clinically useful EGFR inhibition signature, the results confirm the hypothesis that clinically used EGFR inhibitors generate characteristic protein expression changes. This work further outlines a prototypical approach to derive and test protein expression signatures for drug action on signaling networks.

New therapeutics targeting immune checkpoint proteins have significantly advanced treatment of non-small cell lung cancer (NSCLC), but protein level quantitation of drug targets presents a critical problem. We used multiplexed, targeted mass spectrometry (MS) to quantify immunotherapy target proteins PD-1, PD-L1, PD-L2, IDO1, LAG3, TIM3, ICOSLG, VISTA, GITR, and CD40 in formalin-fixed, paraffin-embedded (FFPE) NSCLC specimens. Immunohistochemistry (IHC) and MS measurements for PD-L1 were weakly correlated, but IHC did not distinguish protein abundance differences detected by MS. PD-L2 abundance exceeded PD-L1 in over half the specimens and the drug target proteins all displayed different abundance patterns. mRNA correlated with protein abundance only for PD-1, PD-L1, and IDO1 and tumor mutation burden did not predict abundance of any protein targets. Global proteome analyses identified distinct proteotypes associated with high PD-L1-expressing and high IDO1-expressing NSCLC. MS quantification of multiple drug targets and tissue proteotypes can improve clinical evaluation of immunotherapies for NSCLC.

To facilitate genome-based representation and analysis of proteomics data, we developed a new bioinformatics framework, proBAMsuite, in which a central component is the protein BAM (proBAM) file format for organizing peptide spectrum matches (PSMs)(1) within the context of the genome. proBAMsuite also includes two R packages, proBAMr and proBAMtools, for generating and analyzing proBAM files, respectively. Applying proBAMsuite to three recently published proteomics datasets, we demonstrated its utility in facilitating efficient genome-based sharing, interpretation, and integration of proteomics data. First, the interpretation of proteomics data is significantly enhanced with the rich genomic annotation information. Second, PSMs can be easily reannotated using user-specified gene annotation schemes and assembled into both protein and gene identifications. Third, using the genome as a common reference, proBAMsuite facilitates seamless proteomics and proteogenomics data integration. Finally, proBAM files can be readily visualized in genome browsers and thus bring proteomics data analysis to a general audience beyond the proteomics community. Results from this study establish proBAMsuite as a useful bioinformatics framework for proteomics and proteogenomics research.

Protein alkylation by 4-hydroxy-2-nonenal (HNE), an endogenous lipid derived electrophile, contributes to stress signaling and cellular toxicity. Although previous work has identified protein targets for HNE alkylation, the sequence specificity of alkylation and dynamics in a cellular context remain largely unexplored. We developed a new quantitative chemoproteomic platform, which uses isotopically tagged, photocleavable azido-biotin reagents to selectively capture and quantify the cellular targets labeled by the alkynyl analogue of HNE (aHNE). Our analyses site-specifically identified and quantified 398 aHNE protein alkylation events (386 cysteine sites and 12 histidine sites) in intact cells. This data set expands by at least an order of magnitude the number of such modification sites previously reported. Although adducts formed by Michael addition are thought to be largely irreversible, we found that most aHNE modifications are lost rapidly in situ. Moreover, aHNE adduct turnover occurs only in intact cells and loss rates are site-selective. This quantitative chemoproteomics platform provides a versatile general approach to map bioorthogonal-chemically engineered post-translational modifications and their cellular dynamics in a site-specific and unbiased manner.

Oncogenic mechanisms in small-cell lung cancer remain poorly understood leaving this tumor with the worst prognosis among all lung cancers. Unlike other cancer types, sequencing genomic approaches have been of limited success in small-cell lung cancer, i.e., no mutated oncogenes with potential driver characteristics have emerged, as it is the case for activating mutations of epidermal growth factor receptor in non-small-cell lung cancer. Differential gene expression analysis has also produced SCLC signatures with limited application, since they are generally not robust across datasets. Nonetheless, additional genomic approaches are warranted, due to the increasing availability of suitable small-cell lung cancer datasets. Gene co-expression network approaches are a recent and promising avenue, since they have been successful in identifying gene modules that drive phenotypic traits in several biological systems, including other cancer types.

Agents to induce readthrough of premature termination codons (PTCs) are useful research tools and potential therapeutics. Reporters used to detect PTC readthrough are gene-specific and thus are not suited to for general assessment of readthrough activity or in cases where PTC-inactivated genes are unknown. Here we describe a GFP-based reporter construct pMHG-W57* which is capable of detecting dose-dependent drug-induced PTC readthrough both by fluorescence microscopy and flow cytometry. pMHG-W57* may be used as a general indicator of PTC readthrough in living cells and obviates the need for gene-specific recoding sequences in reporter constructs.

The proteomic effects of specific cancer-related mutations have not been well characterized. In colorectal cancer (CRC), a relatively small number of mutations in key signaling pathways appear to drive tumorigenesis. Mutations in adenomatous polyposis coli (APC), a negative regulator of Wnt signaling, occur in up to 60% of CRC tumors. Here we examine the proteomic consequences of a single gene mutation by using an isogenic CRC cell culture model in which wildtype APC expression has been ectopically restored. Using LC-MS/MS label free shotgun proteomics, over 5000 proteins were identified in SW480Null (mutant APC) and SW480APC (APC restored). We observed 155 significantly differentially expressed proteins between the two cell lines, with 26 proteins showing opposite expression trends relative to gene expression measurements. Protein changes corresponded to previously characterized features of the APCNull phenotype: loss of cell adhesion proteins, increase in cell cycle regulators, alteration in Wnt signaling related proteins, and redistribution of β-catenin. Increased expression of RNA processing and isoprenoid biosynthetic proteins occurred in SW480Null cells. Therefore, shotgun proteomics reveals proteomic differences associated with a single gene change, including many novel differences that fall outside known target pathways.

Protein assembly and biological interpretation of the assembled protein lists are critical steps in shotgun proteomics data analysis. Although most biological functions arise from interactions among proteins, current protein assembly pipelines treat proteins as independent entities. Usually, only individual proteins with strong experimental evidence, that is, confident proteins, are reported, whereas many possible proteins of biological interest are eliminated. We have developed a clique-enrichment approach (CEA) to rescue eliminated proteins by incorporating the relationship among proteins as embedded in a protein interaction network. In several data sets tested, CEA increased protein identification by 8-23% with an estimated accuracy of 85%. Rescued proteins were supported by existing literature or transcriptome profiling studies at similar levels as confident proteins and at a significantly higher level than abandoned ones. Applying CEA on a breast cancer data set, rescued proteins coded by well-known breast cancer genes. In addition, CEA generated a network view of the proteins and helped show the modular organization of proteins that may underpin the molecular mechanisms of the disease.

Cysteine S-sulphenylation provides redox regulation of protein functions, but the global cellular impact of this transient post-translational modification remains unexplored. We describe a chemoproteomic workflow to map and quantify over 1,000 S-sulphenylation sites on more than 700 proteins in intact cells. Quantitative analysis of human cells stimulated with hydrogen peroxide or epidermal growth factor measured hundreds of site selective redox changes. Different cysteines in the same proteins displayed dramatic differences in susceptibility to S-sulphenylation. Newly discovered S-sulphenylations provided mechanistic support for proposed cysteine redox reactions and suggested novel redox mechanisms, including S-sulphenyl-mediated redox regulation of the transcription factor HIF1A by SIRT6. S-sulphenylation is favored at solvent-exposed protein surfaces and is associated with sequence motifs that are distinct from those for other thiol modifications. S-sulphenylations affect regulators of phosphorylation, acetylation and ubiquitylation, which suggest regulatory crosstalk between redox control and signalling pathways.

Cytokines of the interleukin-1 (IL-1) family, such as IL-1 alpha/beta and IL-18, have important functions in host defense, immune regulation, and inflammation. Insight into their biological functions has led to novel therapeutic approaches to treat human inflammatory diseases. Within the IL-1 family, IL-1 alpha/beta, IL-1Ra, and IL-18 have been matched to their respective receptor complexes and have been shown to have distinct biological functions. The most prominent orphan IL-1 receptor is ST 2. This receptor has been described as a negative regulator of Toll-like receptor-IL-1 receptor signaling, but it also functions as an important effector molecule of T helper type 2 responses. We report a member of the IL-1 family, IL-33, which mediates its biological effects via IL-1 receptor ST 2, activates NF-kappaB and MAP kinases, and drives production of T(H)2-associated cytokines from in vitro polarized T(H)2 cells. In vivo, IL-33 induces the expression of IL-4, IL-5, and IL-13 and leads to severe pathological changes in mucosal organs.

Reactive electrophiles generated by lipid peroxidation are thought to contribute to cardiovascular disease and other oxidative stress-related pathologies by covalently modifying proteins and affecting critical protein functions. The difficulty of capturing and analyzing the relatively small fraction of modified proteins complicates identification of the protein targets of lipid electrophiles. We recently synthesized a biotin-modified linoleoylglycerylphosphatidylcholine probe called PLPBSO ( Tallman et al. Chem. Res. Toxicol. 2007, 20, 227-234 ), which forms typical linoleate oxidation products and covalent adducts with model peptides and proteins. Supplementation of human plasma with PLPBSO followed by free radical oxidation resulted in covalent adduction of PLPBSO to plasma proteins, which were isolated with streptavidin and identified by liquid chromatography-tandem mass spectrometry (LC-MS-MS). Among the most highly modified proteins was apolipoprotein A1 (ApoA1), which is the core component of high density lipoprotein (HDL). ApoA1 phospholipid adduct sites were mapped by LC-MS-MS of tryptic peptides following mild base hydrolysis to release esterified phospholipid adducts. Several carboxylated adducts formed from phospholipid-esterified 9,12-dioxo-10( E)-dodecenoic acid (KODA), 9-hydroxy, 12-oxo-10( E)-dodecenoic acid (HODA), 7-oxoheptanoic acid, 8-oxooctanoic acid, and 9-oxononanoic acid were identified. Free radical oxidations of isolated HDL also generated adducts with 4-hydroxynonenal (HNE) and other noncarboxylated electrophiles, but these were only sporadically identified in the PLPBSO-adducted ApoA1, suggesting a low stoichiometry of modification in the phospholipid-adducted protein. Both phospholipid electrophiles and HNE adducted His162, which resides in an ApoA1 domain involved in the activation of Lecithin-cholesterol acyltransferase and maturation of the HDL particle. ApoA1 lipid electrophile adducts may affect protein functions and provide useful biomarkers for oxidative stress.

Integrating computational chemistry and toxicology can improve the read-across analog approach to fill data gaps in chemical safety assessment. In read-across, structure-related parameters are compared between a target chemical with insufficient test data and one or more materials with sufficient data. Recent advances have focused on enhancing the grouping or clustering of chemicals to facilitate toxicity prediction via read-across. Analog selection ascertains relevant features, such as physical-chemical properties, toxicokinetic-related properties (bioavailability, metabolism, and degradation pathways), and toxicodynamic properties of chemicals with an emphasis on mechanisms or modes of action. However, each human health end point (genotoxicity, skin sensitization, phototoxicity, repeated dose toxicity, reproductive toxicity, and local respiratory toxicity) provides a different critical context for analog selection. Here six end point-specific, rule-based schemes are described. Each scheme creates an end point-specific workflow for filling the target material data gap by read-across. These schemes are intended to create a transparent rationale that supports the selected read-across analog(s) for the specific end point under study. This framework can systematically drive the selection of read-across analogs for each end point, thereby accelerating the safety assessment process.

Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this "guilt-by-association" (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies.

Immunohistochemistry (IHC) using formalin-fixed, paraffin embedded (FFPE) tissue is limited by epitope masking, posttranslational modification and immunoreactivity loss that occurs in stored tissue by poorly characterized mechanisms. Conformational epitopes recognized by many programmed-death-ligand-1 (PD-L1) IHC assays are particularly susceptible to degradation and provide an ideal model for understanding signal loss in stored FFPE tissue. Here we assessed 1206 tissue sections to evaluate environmental factors impacting immunoreactivity loss. PD-L1 IHC using four antibodies (22C3, 28-8, E1L3N, and SP142), raised against intracellular and extracellular epitopes, was assessed in stored FFPE tissue alongside quantitative mass spectrometry (MS). Global proteome analyses were used to assess proteome-wide oxidation across an inventory of 3041 protein groups (24,737 distinct peptides). PD-L1 quantitation correlated well with IHC expression on unaged sections (R2 = 0.744; P < 0.001), with MS demonstrating no loss of PD-L1 protein, even in sections with significant signal loss by IHC impacting diagnostic category. Clones 22C3 and 28-8 were most susceptible to signal loss, with E1L3N demonstrating the most robust signal (56%, 58%, and 33% reduction respectively; p < 0.05). Increased humidity and temperature resulted in significant acceleration of immunoreactivity loss, which was mitigated by storage with desiccant. MS demonstrated only modest oxidation of 274 methionine-containing peptides and aligned with IHC results suggesting peptide oxidation is not a major factor. These data imply immunoreactivity loss driven by humidity and temperature results in structural distortion of epitopes rendering them unsuitable for antibody binding following epitope retrieval. Limitations of IHC biomarker analysis from stored tissue sections may be mitigated by cost-effective use of desiccant when appropriate. In some scenarios, complementary MS is a preferred approach for retrospective analyses of archival FFPE tissue collections.

The C terminus of HSC70-interacting protein (CHIP, STUB1) is a ubiquitously expressed cytosolic E3-ubiquitin ligase. CHIP-deficient mice exhibit cardiovascular stress and motor dysfunction before premature death. This phenotype is more consistent with animal models in which master regulators of autophagy are affected rather than with the mild phenotype of classic E3-ubiquitin ligase mutants. The cellular and biochemical events that contribute to neurodegeneration and premature aging in CHIP KO models remain poorly understood. Electron and fluorescent microscopy demonstrates that CHIP deficiency is associated with greater numbers of mitochondria, but these organelles are swollen and misshapen. Acute bioenergetic stress triggers CHIP induction and relocalization to mitochondria, where it plays a role in the removal of damaged organelles. This mitochondrial clearance is required for protection following low-level bioenergetic stress in neurons. CHIP expression overlaps with stabilization of the redox stress sensor PTEN-inducible kinase 1 (PINK1) and is associated with increased LC3-mediated mitophagy. Introducing human promoter-driven vectors with mutations in either the E3 ligase or tetracopeptide repeat domains of CHIP in primary neurons derived from CHIP-null animals enhances CHIP accumulation at mitochondria. Exposure to autophagy inhibitors suggests that the increase in mitochondrial CHIP is likely due to diminished clearance of these CHIP-tagged organelles. Proteomic analysis of WT and CHIP KO mouse brains (four male, four female per genotype) reveals proteins essential for maintaining energetic, redox, and mitochondrial homeostasis undergo significant genotype-dependent expression changes. Together, these data support the use of CHIP-deficient animals as a predictive model of age-related degeneration with selective neuronal proteotoxicity and mitochondrial failure.SIGNIFICANCE STATEMENT Mitochondria are recognized as central determinants of neuronal function and survival. We demonstrate that C terminus of HSC70-Interacting Protein (CHIP) is critical for neuronal responses to stress. CHIP upregulation and localization to mitochondria is required for mitochondrial autophagy (mitophagy). Unlike other disease-associated E3 ligases such as Parkin and Mahogunin, CHIP controls homeostatic and stress-induced removal of mitochondria. Although CHIP deletion results in greater numbers of mitochondria, these organelles have distorted inner membranes without clear cristae. Neuronal cultures derived from animals lacking CHIP are more vulnerable to acute injuries and transient loss of CHIP renders neurons incapable of mounting a protective response after low-level stress. Together, these data suggest that CHIP is an essential regulator of mitochondrial number, cell signaling, and survival.